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  <title>Description of VMT_FilterBS</title>
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  <meta name="description" content="This routine filters the backscatter data.">
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<h1>VMT_FilterBS
</h1>

<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>This routine filters the backscatter data.</strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>function A = VMT_FilterBS(z,A) </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre class="comment"> This routine filters the backscatter data.

 (adapted from code by J. Czuba)

 P.R. Jackson, USGS, 12-9-08</pre></div>

<!-- crossreference -->
<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
This function calls:
<ul style="list-style-image:url(../matlabicon.gif)">
</ul>
This function is called by:
<ul style="list-style-image:url(../matlabicon.gif)">
<li><a href="VMT_PreProcess.html" class="code" title="function A = VMT_PreProcess(z,A)">VMT_PreProcess</a>	This function is a driver to preprocess the transects data.  Several</li></ul>
<!-- crossreference -->



<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function A = VMT_FilterBS(z,A)</a>
0002 <span class="comment">% This routine filters the backscatter data.</span>
0003 <span class="comment">%</span>
0004 <span class="comment">% (adapted from code by J. Czuba)</span>
0005 <span class="comment">%</span>
0006 <span class="comment">% P.R. Jackson, USGS, 12-9-08</span>
0007 
0008 
0009 <span class="comment">%% Filter</span>
0010 <span class="comment">% filter backscatter when climbing walls</span>
0011 
0012 <span class="keyword">for</span> zi = 1 : z
0013 
0014     A(zi).Clean.backstandf=nan(double(A(zi).Sup.nBins),A(zi).Sup.noe);
0015     A(zi).Clean.bsf=nan(double(A(zi).Sup.nBins),A(zi).Sup.noe);
0016 
0017     <span class="comment">% Determine the standard deviation of the backscatter for the four beams in</span>
0018     <span class="comment">% one bin in one ensemble</span>
0019     back=A(zi).Wat.backscatter;
0020     back(back&gt;=255) = NaN;
0021     A(zi).Clean.backstandf = std(back,0,3);
0022 
0023     <span class="comment">% Remove backscatter intensities &gt;= 255 (bad value) and backscatter</span>
0024     <span class="comment">% intensities with a standard deviation greater than 10 (mainly climbing</span>
0025     <span class="comment">% walls)</span>
0026     A(zi).Clean.bsf = nanmean(A(zi).Wat.backscatter,3);
0027     A(zi).Clean.bsf(A(zi).Clean.bsf&gt;=255) = NaN;
0028     <span class="comment">%A(zi).Clean.bsf(A(zi).Clean.backstandf&gt;10)=NaN;  %Removed STD screening PRJ 2-15-11</span>
0029 
0030     A(zi).Nav.depth(A(zi).Nav.depth==-32768)=NaN;
0031 
0032 <span class="keyword">end</span></pre></div>
<hr><address>Generated on Thu 21-Mar-2013 09:32:01 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" target="_parent">m2html</a></strong> &copy; 2005</address>
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